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Negatome specifications

Information


Unique identifier OMICS_02944
Name Negatome
Restrictions to use None
Community driven No
Data access File download, Browse
User data submission Not allowed
Version 2.0
Maintained Yes

Maintainer


  • person_outline Dmitrij Frishman

Publications for Negatome

Negatome citations

 (6)
library_books

Building protein protein interaction networks for Leishmania species through protein structural information

2018
BMC Bioinformatics
PMCID: 5840830
PMID: 29510668
DOI: 10.1186/s12859-018-2105-6

[…] f 119 protein pairs that are known to interact, obtained from the Benchmark 4.0 database [], and to a set of negative interaction data, composed of 147 non-interacting protein pairs obtained from the Negatome database []. Hence, our final training/test dataset was composed by 266 total entries, where the Calibur and PPI-scores were used as feature inputs, and the outputs were set as “1” for intera […]

library_books

Strength of functional signature correlates with effect size in autism

2017
Genome Med
PMCID: 5501949
PMID: 28687074
DOI: 10.1186/s13073-017-0455-8

[…] [] (v2.9), HPRD [] (release 9), HIPPIE [] (v1.8), IntAct [], the CCSB interactome database [] (HI-III v2.2), STRING [] (v10), and PIPs []. A non-interacting PPI network was created from data from the negatome [] (v2). […]

library_books

Across proteome modeling of dimer structures for the bottom up assembly of protein protein interaction networks

2017
BMC Bioinformatics
PMCID: 5427563
PMID: 28499419
DOI: 10.1186/s12859-017-1675-z

[…] imizes the MCC to a value of 0.61 with a true positive rate of 0.81 and a false positive rate of 0.19 (a solid circle in Fig. ). Finally, we independently test our classification protocol against the Negatome 2.0 database, which provides a collection of protein pairs unlikely to physically interact with each other []. We obtained a false positive rate of 0.23, i.e. 23% of non-interacting pairs inc […]

library_books

HVint: A Strategy for Identifying Novel Protein Protein Interactions in Herpes Simplex Virus Type 1*

2016
PMCID: 5013309
PMID: 27384951
DOI: 10.1074/mcp.M116.058552

[…] ative database (not containing viral interactomes) with over 570,000 PPIs (). It was tested on a benchmark of 500 high confidence human PPIs (positive data set) and 397 noninteractions extracted from Negatome (negative data set) (). Around the optimal score cut-offs for each database (0.485 for MIscore, 0.343 for the Mentha score) MIscore was shown to have greater accuracy, precision, and recall t […]

library_books

Comparative study of the effectiveness and limitations of current methods for detecting sequence coevolution

2015
Bioinformatics
PMCID: 4481699
PMID: 25697822
DOI: 10.1093/bioinformatics/btv103

[…] y Table S2) are adopted as a benchmark dataset for a detailed analysis, which is further consolidated by extending the analysis to a dataset of 2330 structurally resolved protein pairs extracted from Negatome 2.0 database () of non-interacting proteins. Two basic performance criteria are considered: first, does the method correctly filter out intermolecular correlations (FPs) if the analyzed pairs […]

library_books

Highly precise protein protein interaction prediction based on consensus between template based and de novo docking methods

2013
BMC Proc
PMCID: 4044902
PMID: 24564962
DOI: 10.1186/1753-6561-7-S7-S6

[…] ted the pair of caspase-3 and caspase-7 with a high score (the final probability value was 0.99). This situation is difficult to avoid in large-scale prediction problems. However, efforts such as the Negatome project [] will help to improve this difficulty in the future. […]

Citations

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Negatome institution(s)
Institute for Bioinformatics and Systems Biology/MIPS, HMGU - German Research Center for Environmental Health, Neuherberg, Germany; Clueda AG, Munich, Germany; Department of Genome Oriented Bioinformatics, Technische Universitaet Muenchen Wissenschaftszentrum Weihenstephan, Freising, Germany
Negatome funding source(s)
Supported by DFG International Research Training Group ‘Regulation and Evolution of Cellular Systems’ [GRK 1563]; the Joint Technology Platform within the Helmholtz Alliance for Systems Biology and the Federal Ministry of Education, Science, Research and Technology [NGFN: 01GR0451, SysMBo, FKZ: 0315494A].

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